Category: Digital Twin

Everyone talks about the Internet of Things (IoT) and the digital twin – they form the framework for new, digital business models. According to a forecast by PwC, digitization will bring the manufacturing industry an increase in turnover of more than 270 billion euros in Germany alone over the next four years.

Companies are hoping for sales growth through smart products and digital business models. This is also confirmed by our current IoT study, which was conducted jointly with the Fraunhofer Institute for Production Systems and Design Technology (IPK) and the Association of German Engineers (VDI). It shows that companies have high expectations, but at the same time makes it clear that there is still a certain reluctance to implement the new legislation in practice. Many companies are faced with the question: “How does it actually work with IoT?”

In my experience, companies often think the second way before taking the first step, which leads to restraint. Of course, it is good and important to have a vision. The picture, which is often published in blogs and forums, usually shows very sophisticated IoT scenarios. They don’t start where many companies currently stand with their business model and technology knowledge.

That’s why it’s important to gain your own experience and gradually approach new digital business models, true to the motto Think big, start small, act now!. Own projects, also together with technology partners, automatically expand the wealth of experience. So why not start using the new technology to support classic business?

With my contribution I would like to show how companies can realize an effective IoT scenario for their business in just 4 steps.

Step 1: The digital twin as a communication interface

The necessary data for the digital twin is usually already available in the company. The first step is a simple serial number. It serves as a documentation interface and connects the data with the product. 3D data is added later. The data is often already available in PLM or ERP systems – for example from production, purchasing or development – and should be displayed in a dashboard.

Step 2: Generate data via sensors

Sensors are also often already available, for example for controlling devices, machines and systems. They record states such as power, pressure, consumption, etc. This data is now consistently recorded and stored suitably. In this way, the current status can always be viewed. In addition, limit values are defined, for example for excessive current consumption, whereupon warnings can be sent and errors rectified.

Step 3: Initiate smart maintenance work

A detailed damage and wear picture can be derived from the analysis of the data and measures such as maintenance projects can be initiated as early as possible. The digital twin serves as a documentation interface. All adjustments to the product thus remain traceable. This data history can later be used for the development of predictions (predictive maintenance). The digital twin as maintained supports the documentation of product changes, can link them with historical data and thus also prove in which configuration the product functions optimally. The classic product lifecycle is thus extended to its usage.

Step 4: Request spare parts

In
addition, the information is used to request spare parts. With the help of
compressed service parts lists or spare parts catalogs, the data is assigned to
the affected component and the required spare part is delivered in the event of
imminent damage. This data is also already stored in ERP systems. This process
can be triggered manually or automatically on the basis of the device messages.
In this way, companies avoid downtime in their own production.

In
these 4 simple steps, an efficient IoT scenario has been implemented and a big
step towards a digital business model has been taken. I am sure that many
companies will be able to get started with the new technology in this way.

So:
Get started and use the experience gained for digital business models!